Neural Mixture Models with Expectation-Maximization for End-to-end Deep Clustering.
Dumindu TisseraKasun VithanageRukshan WijesingheAlex XavierSanath JayasenaSubha FernandoRanga RodrigoPublished in: CoRR (2021)
Keyphrases
- end to end
- mixture model
- expectation maximization
- em algorithm
- k means
- unsupervised learning
- model based clustering
- density estimation
- finite mixture models
- mixture modeling
- overlapping clustering
- finite mixture model
- gaussian mixture model
- generative model
- minimum message length
- probabilistic model
- maximum likelihood
- bayesian information criterion
- clustering algorithm
- finite mixtures
- hierarchical clustering
- gaussian mixture
- network architecture
- admission control
- model selection
- maximum likelihood estimation
- language model
- probability density function
- clustering method
- congestion control
- information theoretic
- cluster analysis
- mixture of gaussians
- application layer
- text classification
- object recognition
- machine learning